Virtually all large scale industrial facilities (or “plants”) require the regular operation and maintenance of a variety of disparate pieces of equipment. These pieces of equipment may operate independently of one and another, or they may operate in concert. For example, virtually every building in the United States has some form of heating and air conditioning system. In a large building, such as a factory or an office building, several pumps, boilers, fans, heat exchangers and other pieces of equipment are typically employed to maintain the temperature and/or humidity at various locations inside the building at desired levels. Typically, the operations of each of these pieces of equipment affect the desired state of other pieces of equipment, either up or downstream, or in parallel. As an example of an operation up or downstream, a building might have several boilers, each connected to a pump. When any one of the boilers is turned on, the pump might also be required to be turned on. As an example of equipment operating in parallel, it might be the case that when one of the boilers in turned on, one or more of the other boilers may be turned down or off.
The controls for these pieces of equipment may be integrated, such that an when an operator changes the operating state of one piece of equipment, the operating state of other pieces of equipment upstream, downstream, or in parallel, are also automatically changed to compensate. Alternatively, the controls may be separate, such that when the operating state of a piece of equipment is altered, an operator is required to make appropriate adjustments to various pieces of equipment manually. The latter circumstance typically requires a high degree of both skill and familiarity with the equipment on the part of the operator.
While many industrial processes have costs that are uniquely associated with the specific process being run in the facility, two main costs are associated with the operation of equipment in virtually all industrial facilities; energy and labor. Energy costs may be incurred for generating power, purchasing power, or consuming power. Accordingly, energy costs may encompass power purchased off the grid, natural gas, oil, or other fuel sources, and the overall efficiency of the plant can cause energy costs to vary significantly. Labor costs are typically related to both operations and maintenance of the facility. Operators who operate the process at something other than optimal efficiency can greatly increase the costs per desired level of output. Similarly, the maintenance of equipment typically requires skilled personnel who are capable of diagnosing and repairing damage or other kinds of wear that are associated with degradations in performance.
Taken together, a system that can maximize the energy efficiency of a plant while minimizing the labor necessary to maintain efficient operations can result in significant cost savings. Not surprisingly, many systems that seek to automate many of the steps required to maximize energy efficiency or to minimize the required labor have been proposed.
For example, U.S. Pat. No. 5,216,623 to Barrett, et al. issued Jun. 1, 1993 and entitled “System and method for monitoring and analyzing energy characteristics” describes a system for monitoring energy characteristics of an energy consuming system. The '623 system includes a data gathering device that accumulates data representing each of the sensed energy characteristics in real time, the data representing magnitude of the sensed energy characteristic as well as the time at which the magnitude is sensed. The data that is accumulated for each of the sensed energy characteristics is periodically transmitted to a remote analysis station. The remote analysis station performs a detailed analysis of the sensed energy characteristics and generates reports containing summaries of the sensed data in the form of listings of compressed data as well as graphs such as histograms and graphs correlating different energy characteristics of the energy consuming system.
As described by the '623 patent, in order to provide a detailed analysis of the data wherein the analysis is not constrained by any on-site limitations, the accumulated sensor data is periodically transmitted to a remote site. At the remote site means are provided to convert the raw accumulated sensor data into standard units of measure so that it can be displayed or printed in a meaningful manner. The data from various sensors is also combined at the remote site to derive data representing additional energy characteristics of the energy consuming system. The '623 patent does contemplate on-site analysis, however, the '623 patent describes as preferred the analysis of the data as occurring off-site. Further, the data from various types of sensors is described as being “statistically correlated at the remote site so that relationships between energy characteristics may be obtained.”
The '623 patent thus suffers from several drawbacks, and presents a less than complete solution to the goal of maximizing energy efficiency of a plant while minimizing the required labor. While the '623 patent describes a method for automating the collection of data, it does not perform analysis of the data, or of identifying the optimal operating conditions for the process.
U.S. Pat. No. 6,278,899 to Piche, et al. issued Aug. 21, 2001 and entitled “Method for on-line optimization of a plant” describes another system using an on-line optimizer for optimization of the operation of a plant with respect to predetermined operating parameters. The '899 patent describes an optimizer including a steady state optimizer for modeling the operation of the plant and for receiving target plant output values and optimization criteria for generating plant input values that are optimized in accordance with the optimization criteria and with respect to predetermined operating parameters. A nonlinear dynamic model is provided for modeling the operation of the plant and providing estimated plant output values that constitute predicted values of the plant outputs. An analyzer measures the real time and actual plant outputs during operation thereof. A difference device then measures the difference between the estimated output of the nonlinear dynamic model and the output of the difference circuit as bias value. This offset value is then applied to an offset device for offsetting the operation of the steady state optimizer by the bias value during on-line operation of the plant.
The method of the '899 patent is shown using the operation of a boiler as an example. As described in '899, this includes the step of measuring the inputs and the outputs of the plant and then mapping a defined plurality of the measured inputs through a predetermined relationship that defines a desired operating parameter of the plant based upon said defined plurality of the measured inputs to intermediate inputs numbering less than the defined plurality of the measured inputs. The intermediate inputs and the inputs not in said defined plurality of the measured inputs are processed through a steady state optimizer to provide optimized intermediate input values for the intermediate inputs and optimized inputs not in the defined plurality of the measured inputs. The optimized intermediate input values are mapped through an inverse of the predetermined relationship to provide an optimized defined plurality of inputs corresponding to the defined plurality of the measured inputs. The optimized defined plurality of inputs and the optimized inputs not in the defined plurality of the measured inputs are then applied to the plant.
The '899 patent thus suffers from the drawback that it is limited to optimizing inputs. Thus, it is unable to analyze the cause of abnormal operations, such as is required for preventative maintenance and repairs.
U.S. Pat. No. 6,366,889 to Zaloom issued Apr. 2, 2002 entitled “Optimizing operational efficiency and reducing costs of major energy system at large facilities” describes a computer implemented system and method for enhancing the operational efficiency of major energy consuming systems at large facilities. The system and method allows for visually analyzing current and historic patterns of energy consumption in a facility (such as electricity, gas, steam, water or other energy) to determine the presence of possible operating errors, equipment problems, or hard-to-detect billing errors. An important step of the method is creating documented patterns representing unusual circumstances which could represent inefficient operation of the facility, for which solutions are known based on analysis of energy consumption by several large facilities over long periods, to allow identification of the nature of similarly inefficient facility operation as shown in the graphs produced by the disclosed method and to allow identification of possible solutions.
While the '889 patent seeks to solve many of the same problems of the present invention, it does so in a decidedly less sophisticated and less detailed manner. The '889 patent tracks inefficiencies in energy consumption within a facility over multiple periods, and then creates “documented patterns representing unusual circumstances which could represent inefficient operation of the facility, for which solutions are known based on analysis of energy consumption by several large facilities over long periods, to allow identification of the nature of similarly inefficient facility operation as shown in the graphs produced by the system to allow identification of possible solutions.” Accordingly, the '889 patent still requires skilled operations and maintenance personnel who are capable of interpreting the patterns to identify possible solutions.
U.S. Pat. No. 5,061,916 to French, et al. issued Oct. 29, 1991 entitled “Event driven remote graphical reporting of building automation system parameters” describes a system and method for reporting of alarms (or other conditions) to a remote location, in a building automation system. The alarm is reported in graphical format which shows not only the information related directly to the alarm, but also additional information, including graphical information, intended to put the alarm in context. The system provides the user the ability to specify a transmittable alarm, and to define a graphical message for that alarm which includes fixed or static building parameters associated with real time building operating parameters. Upon occurrence of an alarm condition, the system assembles a graphical display for transmission which includes the specified fixed parameters and measured data for the real time operating parameters. The system assures that data is collected and assembled into the graphic display for all specified real time operating parameters, then initiates a facsimile transmission of the graphic display to a remote location.
The '916 patent thus describes a highly detailed alarm system, but while the triggers in the '916 patent alert an operator to component failures, the '916 patent fails to provide any means for analyzing the operating condition of a system, and instead replies on a skilled operator for that function.
U.S. Pat. No. 6,216,956 to Ehlers, et al. issued Apr. 17, 2001 entitled “Environmental condition control and energy management system and method” describes an indoor environmental condition control and energy management system that includes a plurality of inputs. As described by the '956 patent, a user input receives user input parameters including a desired indoor environmental condition range for at least one energy unit price point. An indoor environmental condition input receives a sensed indoor environmental condition. An energy price input receives a schedule of projected energy unit prices per time periods. A processor, coupled to the inputs, computes an environmental condition deadband range for multiple energy unit price points based on the user input parameters and controls at least one energy-consuming load device to maintain the indoor environmental condition within the computed deadband range for a then-current energy unit price point. In an embodiment, the environmental condition includes at least temperature and at least one load device includes a heating and cooling system. The processor, in one embodiment, communicates through a communications link with at least one energy supply company and selects one energy supply company for a premise to minimize energy consumption cost.
While the '956 patent does disclose methods for analyzing and balancing loads to improve efficiency, it does so in a manner that still requires skilled operator and maintenance personnel to monitor and analyze the system. For example, the '956 patent describes its approach as follows: “To illustrate this point, water may be heated in a dual fuel water heater using either gas or electricity as a direct energy unit source. Water may also be heated using a heat recovery system attached to the air heating and cooling system. The system will have the ability to perform the necessary economic modeling to determine if water should be heated directly using the cheapest form of energy unit available (i.e. electricity or gas), or by operating the heating and cooling system, or a combination of the two.”
Accordingly, the '956 patent does not measure the parameters necessary to characterize the actual operating condition of the process, or provide any automated analysis of the actual operating condition.
U.S. Pat. No. 5,159,562 to Putman, et al. issued Oct. 27, 1992 entitled “Optimization of a plurality of multiple-fuel fired boilers using iterated linear programming” describes a method for optimizing control of a process having interdependent operating conditions determined by a control unit, by defining relationships between the operating conditions, all constraints on the process and a process variable to be optimized, in a linear programming matrix; assigning initial values to matrix elements in the liner programming matrix; executing a computer program to solve the linear programming matrix; modifying selected matrix elements representing a set of the operating conditions according to a test strategy and adjusting any unselected matrix elements that require change due to the modifying; executing the computer program to produce a solution of the linear programming matrix after completing the modifying; repeating the modifying and executing of the computer program on the modified linear programming matrix for each test defined by the test strategy until convergence of the solution of the linear programming matrix; and adjusting the control unit to establish the operating conditions indicated by the solution of the linear programming matrix resulting at the convergence.
An example of the '562 patent is shown by optimizing the production of steam and electricity by a system having a gas turbo generator, a steam generator and a heat recovery steam generator. In this application, the '562 patent describes the linear programming matrix as including energy balance equations for the system. The selected matrix elements are modified by calculating first values representing a first steady state model based on the initial solution of the linear programming matrix and second values representing a second steady state model based upon slight modifications to the initial solution. The first values are assigned to the selected matrix elements representing the first steady state model and local linear models determined as a function of the assignment made by the first steady state model are assigned to the selected matrix elements which represent effects of change from conditions in the first steady state model. The modification and execution steps are repeated until an accurate model is being used for the system to produce steam and electricity with optimal settings.
As described by the '562 patent, optimum operating conditions are calculated in an iterative fashion by solving a matrix of linear equations that take into account such variables as fuel cost, fuel efficiency, and the like. Thus, the '562 patent relies on the solution from a matrix of linear equations to correct variances from an optimal level, and thus relies on skilled maintenance and operations personnel to determine the logical structures specific to particular devices and best engineering practices.
Thus, there remains a need for a system that can reduce the costs associated with the operation of equipment in an industrial facility by automating the process of determining the level of operations for optimal efficiency and by automating the process of diagnosing damage or other kinds of wear that are associated with degradations in performance.